Ontology type: schema:ScholarlyArticle Open Access: True
2012-12
AUTHORSChristian Colmsee, Martin Mascher, Tobias Czauderna, Anja Hartmann, Urte Schlüter, Nina Zellerhoff, Jessica Schmitz, Andrea Bräutigam, Thea R Pick, Philipp Alter, Manfred Gahrtz, Sandra Witt, Alisdair R Fernie, Frederik Börnke, Holger Fahnenstich, Marcel Bucher, Thomas Dresselhaus, Andreas PM Weber, Falk Schreiber, Uwe Scholz, Uwe Sonnewald
ABSTRACTBACKGROUND: Maize is a major crop plant, grown for human and animal nutrition, as well as a renewable resource for bioenergy. When looking at the problems of limited fossil fuels, the growth of the world's population or the world's climate change, it is important to find ways to increase the yield and biomass of maize and to study how it reacts to specific abiotic and biotic stress situations. Within the OPTIMAS systems biology project maize plants were grown under a large set of controlled stress conditions, phenotypically characterised and plant material was harvested to analyse the effect of specific environmental conditions or developmental stages. Transcriptomic, metabolomic, ionomic and proteomic parameters were measured from the same plant material allowing the comparison of results across different omics domains. A data warehouse was developed to store experimental data as well as analysis results of the performed experiments. DESCRIPTION: The OPTIMAS Data Warehouse (OPTIMAS-DW) is a comprehensive data collection for maize and integrates data from different data domains such as transcriptomics, metabolomics, ionomics, proteomics and phenomics. Within the OPTIMAS project, a 44K oligo chip was designed and annotated to describe the functions of the selected unigenes. Several treatment- and plant growth stage experiments were performed and measured data were filled into data templates and imported into the data warehouse by a Java based import tool. A web interface allows users to browse through all stored experiment data in OPTIMAS-DW including all data domains. Furthermore, the user can filter the data to extract information of particular interest. All data can be exported into different file formats for further data analysis and visualisation. The data analysis integrates data from different data domains and enables the user to find answers to different systems biology questions. Finally, maize specific pathway information is provided. CONCLUSIONS: With OPTIMAS-DW a data warehouse for maize was established, which is able to handle different data domains, comprises several analysis results that will support researchers within their work and supports systems biological research in particular. The system is available at http://www.optimas-bioenergy.org/optimas_dw. More... »
PAGES245
http://scigraph.springernature.com/pub.10.1186/1471-2229-12-245
DOIhttp://dx.doi.org/10.1186/1471-2229-12-245
DIMENSIONShttps://app.dimensions.ai/details/publication/pub.1029923822
PUBMEDhttps://www.ncbi.nlm.nih.gov/pubmed/23272737
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"description": "BACKGROUND: Maize is a major crop plant, grown for human and animal nutrition, as well as a renewable resource for bioenergy. When looking at the problems of limited fossil fuels, the growth of the world's population or the world's climate change, it is important to find ways to increase the yield and biomass of maize and to study how it reacts to specific abiotic and biotic stress situations. Within the OPTIMAS systems biology project maize plants were grown under a large set of controlled stress conditions, phenotypically characterised and plant material was harvested to analyse the effect of specific environmental conditions or developmental stages. Transcriptomic, metabolomic, ionomic and proteomic parameters were measured from the same plant material allowing the comparison of results across different omics domains. A data warehouse was developed to store experimental data as well as analysis results of the performed experiments.\nDESCRIPTION: The OPTIMAS Data Warehouse (OPTIMAS-DW) is a comprehensive data collection for maize and integrates data from different data domains such as transcriptomics, metabolomics, ionomics, proteomics and phenomics. Within the OPTIMAS project, a 44K oligo chip was designed and annotated to describe the functions of the selected unigenes. Several treatment- and plant growth stage experiments were performed and measured data were filled into data templates and imported into the data warehouse by a Java based import tool. A web interface allows users to browse through all stored experiment data in OPTIMAS-DW including all data domains. Furthermore, the user can filter the data to extract information of particular interest. All data can be exported into different file formats for further data analysis and visualisation. The data analysis integrates data from different data domains and enables the user to find answers to different systems biology questions. Finally, maize specific pathway information is provided.\nCONCLUSIONS: With OPTIMAS-DW a data warehouse for maize was established, which is able to handle different data domains, comprises several analysis results that will support researchers within their work and supports systems biological research in particular. The system is available at http://www.optimas-bioenergy.org/optimas_dw.",
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]Download the RDF metadata as: json-ld nt turtle xml License info
JSON-LD is a popular format for linked data which is fully compatible with JSON.
curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1186/1471-2229-12-245'
N-Triples is a line-based linked data format ideal for batch operations.
curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1186/1471-2229-12-245'
Turtle is a human-readable linked data format.
curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1186/1471-2229-12-245'
RDF/XML is a standard XML format for linked data.
curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1186/1471-2229-12-245'
This table displays all metadata directly associated to this object as RDF triples.
348 TRIPLES
21 PREDICATES
61 URIs
29 LITERALS
17 BLANK NODES